Relationship between exports, imports, and economic growth in France: evidence from cointegration analysis and Granger causality with using geostatistical models
This paper introduces a new way of investigating linear and nonlinear Granger causality between exports, imports and economic growth in France over the period 1961-2006 with using geostatistical models (kiriging and inverse distance weighting). Geostatistical methods are the ordinary methods for forecasting the locations and making map in water engineerig, environment, environmental pollution, mining, ecology, geology and geography. Although, this is the first time which geostatistics knowledge is used for economic analyzes. In classical econometrics there do not exist any estimator which have the capability to find the best functional form in the estimation. Geostatistical models investigate simultaneous linear and various nonlinear types of causality test, which cause to decrease the effects of choosing functional form in autoregressive model. This approach imitates the Granger definition and structure but improve it to have better ability to investigate nonlinear causality. Results of both VEC and Improved-VEC (with geostatistical methods) are similar and show existance of long run unidirectional causality from exports and imports to economic growth. However the F-statistic of improved-VEC is larger than VEC indicating that there are some exponential and spherical functions in the VEC structure instead of the linear form.
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